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An Idea Sparked In the San Francisco Lab Evolves

For patients, there are more wearable technologies available than ever. Have a sleep condition? Need a heart monitor? Require help tracking symptoms of a chronic condition? Patients, providers, and researchers have so many devices at their disposal that it’s often tough to figure out which one would be the best match for a specific condition.

Project HoneyBee was founded with the understanding that there needed to be a robust, evidence-based filtering and validation mechanism for biosensors for in order for them to live up to their potential to detect, diagnose, and prevent disease as gatherers of continuous rather than episodic physiological data. The Phoenix-based initiative from Arizona State University has developed a database containing more than 200 wearable technologies. By conducting observational clinical trials and pulling in scholarly research on the devices, Project HoneyBee is developing new ways to assess not only the devices’ effectiveness, but also how they match up with clinician workflow and patients’ individual needs.

Initially, the Project HoneyBee device database was aimed at helping clinicians. It currently acts as a sort of consultant and intermediary between the clinician and the available technologies. When a patient comes into the clinic with, say, a heart condition or a sleep disorder that needs monitoring, the clinician will consult Project HoneyBee. Based on filters set up around the patient’s physiological parameters, Project HoneyBee will run a query of their database, returning a ranked list of the devices that best match the patient’s needs. It’s an incredibly powerful evidence-based resource—especially since most biosensors have yet to receive FDA approval.

But recently, inspired by the San Francisco Lab and its participants, the HoneyBee Team began thinking about how the initiative might flip the resource’s intended audience, opening it up to patients. An open-source database presenting quality, personalized information in real-time matching patient with biosensor does not yet exist. In working through this idea, the team saw a positive feedback loop emerge. With access to Project HoneyBee’s database, patients could make more informed decisions about their own health. And more knowledgeable patients—and the user feedback they provide—would transform Project HoneyBee’s device database into a novel learning platform that promotes trust and collaborative care between patients and their health care team.

To realize this potential, Project HoneyBee needs to develop a public-facing site that would allow patients to dig into the existing database, filter results, and print out recommendations to share with their clinician. Ideally the expansion leads to enhanced patient-provider communication and improved overall health. Find their Flip idea here.